Statistical evaluation of remotely sensed data for water quality monitoring

The primary objective of this study was to determine relationships between water quality parameters (WQPs) and digital data from the Landsat satellite to estimate and map the WQP in the Porsuk Dam reservoir. Suspended sediments (SS), chlorophyll a (chl-a), NO₃-N and transmitted light intensity depth (TLID) were the parameters for water quality determination used in this study. Collection of these data, obtained from the General Directorate of State Hydraulic Works (GDSHW) was synchronized with the Landsat satellite overpass of the September 1987. The relationships between the brightness values (BV) of the TM data and WQP were determined. Using the TM data, we developed multiple regression equations to estimate the WQPs, and the validation of these equations was checked by using ANOVA. The effects of SS, NO₃-N and chl-a on TLID were tested not only for ground data, but also for TM datasets. Regression equations were developed for two different datasets and the homogeneity of those equations was tested. Finally, these regression equations evaluated from digital TM data and ground data were applied to map TLID values.     

Representing time intervals in a two-dimensional space: An empirical study

ObjectiveInstead of the linear model (LM), time intervals can be represented by a two-dimensional (2D) model, which is called the triangular model (TM). Although the TM has been introduced for decades and applied in some areas, there still a lack of empirical studies on its usability. To fill this gap, this study aims to evaluate how people perform when using the TM to answer questions on time intervals, in comparison with using the traditional LM.MethodAround 250 novice participants took part in the experiment, which consisted of a video training, a pretest and posttest. The video training introduced the basic knowledge of temporal relations and the two representations. The pretest allowed participants to practice the knowledge they have learned and receive feedbacks of the answers. In the posttest, participants' accuracy and speed when answering the questions were recorded for analysis. The results of using the TM and the LM were compared in pairs. The null hypothesis is that the participants produce equal results with the two models.ResultThe results showed that the participants scored better and spent less time when answering questions with the TM, which rejected the null hypothesis. Moreover, the score and speed when they used the TM did decline in the questions containing a larger number of intervals. In contrast, the score and accuracy when they used the LM declined when questions containing a large number of intervals.Conclusion

• •The TM is easy to learn. After a 20-min training, novice participants can use it to solve questions and produce satisfactory result.
• •The TM is easy and efficient for visual queries of time intervals.
• •The TM is easy to use for handling a large number of intervals.

Implication

• •The TM can be widely applied in analysing time intervals and linear data.
• •Tools implementing the TM can be learned and used by novice users.

     

A comparison of SPOT and Landsat-TM data for use in conducting inventories of forest resources

Abstract

SPOT multispectral (XS) and Landsat Thematic Mapper (TM) digital data were studied in an attempt to evaluate the use of this data in detailed assessments of forest conditions. Forest type, basal area, and age class information were collected from 256 sample sites within an intensively managed 80000acre experimental forest in North Carolina, U.S.A. A comparison of the SPOT and TM data with the sample site information showed that XS3, the near-infrared waveband, and TM bands 2, 3, 4, 5, and 7 were significantly correlated with basal area. Age class was not found to be significantly correlated with any of the three SPOT XS wavebands. TM bands 2, 3, 4, 5, and 7 were, however, shown to be significantly correlated with age class. Although significant, the correlation coefficients between the TM or SPOT waveband data and basal area or age class were low (<0.65).

Six forest cover types, and an additional water category, were selected as the basis of a land cover classification system for use with the TM and SPOT data. Verification of the classification of the seven cover types using the SPOT XS waveband data resulted in an estimated accuracy of 74.4 per cent. Classification accuracy was slightly reduced (70.8 per cent) when the TM wavebands corresponding to the SPOT XS bands were used as inputs to the classifier. When each of the six visible and reflective infrared TM wavebands were included in the classification process overall accuracy increased to 885 per cent.     

Evaluation of the potential of the Thematic Mapper for marine application

Abstract

The potential of the Thematic Mapper (TM) on board Landsal-5 for marine applications has been investigated with reference to the well-known performance of the Coastal Zone Color Scanner of Nimbus-7. The study consisted of (a) a sensitivity analysis, considering such fundamental error sources as retrieval algorithm sensitivity, atmospheric correclion, instrument noise and signal digitization and (b) the interpretation of a TM scene by the procedure suggested in (a). The evidence provided by the experimental test validated the positive conclusions of the theoretical work, indicating that the analysis of TM bands 1 to 4 data should be capable of yielding quantitative information of satisfactory quality on fundamental water quality parameters, such as chlorophyll (i.e. phytoplankion) and suspended sediment concentrations.     

Cover The 1992 Etna lava flow imaged by Landsat TM

Abstract

This paper describes an experiment where sea water quality parameters were determined using data from the Landsat Thematic Mapper (TM) satellite remote sensing system over a coastal sewage outfall area. The parameters determined included turbidity, chlorophyll-a, chlorophyll-i, phaeopigment and total pigment. The area investigated was a sewage outfall site off the North Head of Sydney Harbour, Australia. The method used multiple regression to relate site sampled parameters to digital Landsat-TM data, and the results verified using data not used in the regression. Multiple correlation coefficients in excess of R = 0. 9 resulted from the regression analysis, which used Landsat-TM variables in a Chebyshev Series form. However due to the limited number of ocean samples only the results for turbidity were considered significant. Nevertheless a satisfactory methodology is proposed.     

Development of principal component analysis applied to multitemporal Landsat TM data

Abstract

A method of extracting different crop information more effectively, by applying principal component analysis to a three-dimensional three-date Landsat TM data space, has been developed. Landsat TM data obtained on 7 June, 9 July and 26 August 1984 were used to examine the approach, and the results fully demonstrated its advantages over other methods of keeping classification accuracy without any calibrations for multitemporal Landsat data.     

Assessment of grassland degradation near Lake Qinghai,West China,using Landsat TM and in situ reflectance spectra data

The severity of grassland degradation near Lake Qinghai, West China was assessed from a Landsat Thematic Mapper (TM) image in conjunction with in situ samples of per cent grass cover and proportion (by weight) of unpalatable grasses (PUG) collected over 1?m² sampling plots. Spectral reflectance at each sampling plot was measured with a spectrometer and its location determined with a Global Positioning System (GPS) receiver. After radiometric calibration, the TM image was geometrically rectified. Ten vegetation indices were derived from TM bands 3 and 4, and from the spectral reflectance data at wavelengths corresponding most closely to those of TM3 and TM4. Regression analyses showed that NDVI and SAVI are the most reliable indicators of grass cover and PUG, respectively. Significant relationships between TM bands-derived indices and in situ sampled grass parameters were established only after the former had been calibrated with in situ reflectance spectra data. Through the established regression models the TM image was converted into maps of grass cover parameters. These maps were merged to form a degradation map at an accuracy of 91.7%. It was concluded that TM imagery, in conjunction with in situ grass samples and reflectance spectra data, enabled the efficient and accurate assessment of grassland degradation inside the study area.     

Assessment of atmospheric correction methods for Landsat TM data applicable to Amazon basin LBA research

Atmospheric correction is an important preprocessing step required in many remote sensing applications. The authors are engaged in the project 'Human Dimensions of Amazonia: Forest Regeneration and Landscape Structure' in NASA/INPE's Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) programme. This project requires use of corrected Landsat TM data since research foci integrate ground-based data and TM to: (1) measure and model biomass; (2) classify multiple stages of secondary succession; (3) model land cover/land use changes; and (4) derive spectral signatures consistent across different study areas. The 30+ scenes of TM data are historic and lack detailed atmospheric data needed by physically-based atmospheric correction models such as 6S (Second Simulation of the Satellite Signal in the Solar Spectrum). Imagebased DOS models are based on image measurements and explored in this article for application to LBA study areas. Two methods using theoretical spectral radiance and image acquisition date respectively were used to convert TM DN values to at-satellite radiance. Three image-based models were employed using each method to convert at-satellite radiance to surface reflectance. Analyses of these six different image-based models were conducted. The Improved Imagebased DOS was the best technique for correcting atmospheric effects in this LBA research with results similar to those obtained from physically-based approaches.     

The topographic effect on LANDSAT data in gently undulating terrain in southern Sweden

Abstract

The purpose of this study was to investigate the effect of topography on LANDSAT satellite data in gently undulating terrain. Gently undulating terrain is in this work defined as terrain dominated by slopes of between 1° and 15°. For three various solar elevations (38°, 44° and 52°) digital LANDSAT MSS and TM data were merged with digital elevation data. In an agricultural region in southern Sweden 135 cultivated fields, 50 pasture sites and 117 forest sites with a total number of 88 800 pixels were studied.The relationship between LANDSAT response variation and topographic parameters within cultivated fields and forest areas was weak. For some pasture covers a topographic effect was identified.     

Synergistic effects of combined Landsat-TM and SIR-B data for forest resources assessment

Abstract

Three different incidence angle data sets, obtained by the Shuttle Imaging Radar-B in October 1984 over a forested area in northern Florida, were combined with Landsat-5 Thematic Mapper data, to create a digitally registered 10 channel optical/microwave data set. The work discussed in this paper involved the analysis of the data obtained by the two sensors separately and in combination, to determine if there are synergistic effects obtained through the simultaneous use of data obtained from both the optical and microwave portion of the spectrum. The radar data were filtered with a low-pass filter to eliminate the speckle noise. Classifications of the TM, SIR-B and combined TM +SIR-B data sets were performed with both per-point and contextual classifiers. The results showed that filtered radar data can be used to classify accurately major cover types (i.e., pine forest, swamplands and radar smooth targets) and that the contextual classifier provided better classification performance. The combined TM and SIR-B data provided statistically improved classification performances compared to classifications from the three incidence angle SIR-B data, or the TM data alone. A four band subset (TM-2, TM-4, TM-5, and SIR-B 28°) of the 10 channels of the combined TM and SIR-B data set provided higher classification performances (91 per cent overall performance) than the 10 channel data set (86 per cent overall performance).     

Radiometric comparison of the LANDSAT-5 TM and MSS sensors

Abstract

This paper analyses the radiometric accuracy of LANDSAT-5 Thematic Mapper (TM) data and of LANDSAT-5 Multispectral Scanner (MSS) data, using concurrent TM and MSS images recorded simultaneously over the city of Montreal, Quebec, Canada. The data sets were obtained from the Canada Centre for Remote Sensing (CCRS), and have been preprocessed for geometric correction, and for radiometric 23calibration utilizing the in-flight calibration lamp data. The comparison of the TM and MSS normalized apparent reflectances computed for 12 different typical cover types using the post-launch calibration dynamic ranges shows the relevance of the CCRS processing systems. The significant linear regressions, obtained between channels from the two sensors, and the analysis of the ground reflectance corrected for atmospheric absorption and scattering as well as for pixel adjacency effects, can serve both to assess detector degradation with time and to rescale data to match those from other LANDSAT sensors.     

Remote sensing of phytoplankton An attempt from the Landsat Thematic Mapper

Abstract

An atmospheric correction scheme using Landsat Thematic Mapper (TM) bands 1, 2 and 4 was developed and the data corrected for atmospheric effects due to Rayleigh scattering and aerosols. Secondly phytoplankton pigment mapping was achieved through substitution of corrected radiances in TM bands 1 and 2 into a bio-optical algorithm developed for the study area off Azhikal in the Arabian Sea. A C map showing near-surface concentrations of phytoplankton pigments (mgm_?3)and a K map showing the pigment distribution (m?1) in one attenuation length were generated.     

The use of TM data for the study of a modern deltaic depositional system

Abstract

TM data have been used to study the deltaic depositional systems of the Po and Adige rivers. The identification of sedimentary bodies hat have formed in well-defined depositional environments requires the reconstruction of their morphology. To this end, several interactive processing techniques have been applied to a large volume of Thematic Mapper (TM) data relative to different spectral bands and acquisition dates. When necessary, data integration has also been made. Association of genetically related depositional elements allowed the interpretation of depositional environments and developmental stages in the study area.     

A preliminary assessment of Landsat TM imagery for mapping vegetation and sediment distribution in the Wash estuary

Abstract

Analysis of Landsat Thematic Mapper (TM) image of 14 May 1984 has shown that such data can be used to survey vegetation and sediment distributions in the intertidal zone of the Wash estuary at a spatial detail comparable with current methods practised by the.Nature Conservancy Council. Multispectral classification of this TM image showed good separation of salt-marsh vegetation communities which had recently been surveyed by the Nature Conservancy Council and for which reliable training data could be taken. The sensitivity of classification performance, using both parametric and non-parametric algorithms, to apparently minor differences in phenology at training site locations demonstrates two requirements for improved salt-marsh classification. They are the need for strict definition of training data and that TM wave bands 2, 3, 4 and 5 provide suitable spectral vectors for classifying intertidal environments.     

Leaf water stress detection utilizing thematic mapper bands 3, 4 and 5 in soybean plants

Abstract

Foliar water stress in a mature soybean canopy, manifested as wilt rather than as a reflectance shift, was studied using reflectance measurements for Thematic Mapper bands 3 (0.63-0.69 μm), 4 (0.76-0.90 μm) and 5 (1.55-1.75μm). Diffuse and total reflectances were determined using polarization measurements and compared statistically at a variety of look angles at 15min intervals from about 09.00 until 14.00 hours EST. Plots of the data from unstressed canopy show that the behaviour of both the diffuse and total reflectances mimics that of the solar radiance curve with time of day, whereas the stressed canopy reflectance data revealed a nearly linear behaviour with a small negative slope. For both the diffuse and total reflectances measured in the nadir position, TM4 was found to be the most responsive spectral band for foliar water stress detection when the water deficit was sufficient to cause wilting, implying that substantial changes in canopy leaf geometry can best be monitored by TM4. TM3 was not found as responsive to the level of foliar water stress which occurred during this investigation. TM5 showed a response intermediate between TM4 and TM3. The results of polarization calculations for TM4 indicated that during the process of wilting, the level of canopy polarization gradually decreased.     

Radiometric resolution for monitoring vegetation How many bits are needed?

Abstract

The number of radiometric quantizing levels required for satellite monitoring of vegetation resources was evaluated by using in situ collected spectral reflectance data, an atmospheric radiative transfer simulation model and a satellite sensor simulation model. Reflectance data were converted to radiance data; passed through a model atmosphere to an altitude of 706 km; and subsequently quantized at 16,32,64,128,256 and 512 digital count levels for Thematic Mapper bands TM3 (0·63-0·69 μm) and TM4 (0·76-0·90 μm), The simulated digital count data were regressed against in situ biological data to quantify the relationship(s) between quantizing levels.

Results of the analysis demonstrated that solar zenith angle had an effect on QEΔρ, that 256 quantizing levels gave a 1-3 per cent improvement per channel over 64 quantizing levels, and that 256 quantizing levels gave a 1 per cent improvement per channel over 128 quantizing levels. No improvements were found for 256 versus 512 quantizing levels.     

Landscape-scale characterization of cropland in China using Vegetation and Landsat TM images

In this landscape-scale study we explored the potential for multitemporal 10-day composite data from the Vegetation sensor to characterize land cover types, in combination with Landsat TM image and agricultural census data. The study area (175 km by 165 km) is located in eastern Jiangsu Province, China. The Normalized Difference Vegetation Index (NDVI ) and the Normalized Difference Water Index (NDWI ) were calculated for seven 10-day composite (VGT-S10) data from 11 March to 20 May 1999. Multi-temporal NDVI and NDWI were visually examined and used for unsupervised classification. The resultant VGT classification map at 1 km resolution was compared to the TM classification map derived from unsupervised classification of a Landsat 5 TM image acquired on 26 April 1996 at 30 m resolution to quantify percent fraction of cropland within a 1 km VGT pixel; resulting in a mean of 60% for pixels classified as cropland, and 47% for pixels classified as cropland/natural vegetation mosaic. The estimates of cropland area from VGT data and TM image were also aggregated to county-level, using an administrative county map, and then compared to the 1995 county-level agricultural census data. This landscape-scale analysis incorporated image classification (e.g. coarse-resolution VGT data, fineresolution TM data), statistical census data (e.g. county-level agricultural census data) and a geographical information system (e.g. an administrative county map), and demonstrated the potential of multi-temporal VGT data for mapping of croplands across various spatial scales from landscape to region. This analysis also illustrated some of the limitations of per-pixel classification at the 1 km resolution for a heterogeneous landscape.     

Technical note GPS location data An aid to satellite image analyses of poorly mapped regions

Abstract

In inaccessible and highly heterogeneous areas where aerial photography and accurate up-to-date topographic maps are unavailable and where suitable features for ground-based navigation by triangulation are absent, accurately locating ground truth sites and then integrating the field data with digital imagery is often extremely difficult. The advent of the satellite global positioning system (GPS) offers a solution to this problem. Over a 6 month period a battery powered, solar recharged, backpack mounted GPS was used to collect the precise location data essential to the ground truth component of a Landsat Thematic Mapper (TM) landcover classification of the Ituri rain forest of northeastern Zaire. Three-dimensional locations were readily obtained in forest openings > 0·125 ha where the angle to the horizon did not exceed 50^° and canopy closure was less than 30 per cent. GPS location data are presently being used to reference a TM scene geographically and to assign pixels to appropriate landcover classes accurately.     

Subpixel measurement of tropical forest cover using AVHRR data

Abstract

Tropical forest assessment using data from the Advanced Very High Resolution Radiometer (AVHRR) may lead to inaccurate estimates of forest cover in regions of small subpixel forest or non-forest patches and in regions where the pattern of clearance is particularly convoluted. Test sites typifying these two patterns were chosen in Ghana and Rondonia, respectively. To capture the subpixel proportions of forest cover, a linear mixture model was applied to two AVHRR test images over the test sites. The model produced image outputs in which pixel intensities indicated the proporton of forest cover per km². For comparison, supervised maximum likelihood classifications were also performed. The outputs were assessed against classified Landsat TM scenes, converted to proportions maps and coregistered to the AVHRR images. An empirical method was applied for determining the critical forest cover per km² needed for an AVHRR pixel to be classified as forest. The critical values exceeded 50 per cent, indicating a tendency for AVHRR classification to underestimate forest cover. This was confirmed by comparing estimates of total forest cover obtained from the AVHRR and TM classifications. In the case of Ghana, a more accurate estimate of forest cover was obtained from the AVHRR mixture model than from the classification. Both mixture model outputs were found to be well correlated with those from Landsat TM. Further work should test the robustness of the approach adopted here when applied to much larger areas.     

Statistical problems in the discrimination of land cover from satellite images: a case study in lowland Britain

Abstract

This paper discusses underlying statistical problems in identifying land classes from satellite imagery. Problems in assessing accuracy of automatic classifiers are illustrated using results from analysis of two Landsat Thematic mapper (TM) subscenes collected for the same areas within Cambridgeshire in the summer and autumn of 1984. Problems arising from between-site variability of training sites are discussed. Use of rejection thresholds is also discussed. Recommendations are given for improving choice of training data to attempt lo overcome some of these problems.